GMS location: 1416

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.065 0.310 0.391 2.601 NaN NaN
forest winter 2016 0.994 0.065 0.264 0.358 2.470 0.472 2.942
baseline winter 2017 0.991 0.065 0.348 0.399 2.553 NaN NaN
forest winter 2017 0.991 0.065 0.272 0.367 2.316 0.472 2.707
baseline winter 2018 0.986 0.026 0.401 0.428 3.200 NaN NaN
forest winter 2018 0.978 0.026 0.329 0.374 3.149 0.476 4.164
baseline winter 2019 0.986 0.053 0.327 0.431 1.757 NaN NaN
forest winter 2019 0.993 0.053 0.252 0.384 1.370 0.458 2.590
baseline all 0.989 0.052 0.345 0.411 3.200 NaN NaN
forest all 0.989 0.052 0.280 0.370 3.149 0.470 3.119

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.065 0.310 0.391 2.601 NaN NaN
elr winter 2016 0.994 0.065 0.267 0.367 2.388 0.550 4.672
baseline winter 2017 0.991 0.065 0.348 0.399 2.553 NaN NaN
elr winter 2017 0.981 0.065 0.326 0.418 2.303 0.532 4.493
baseline winter 2018 0.986 0.026 0.401 0.428 3.200 NaN NaN
elr winter 2018 0.978 0.026 0.338 0.413 2.928 0.553 5.084
baseline winter 2019 0.986 0.053 0.327 0.431 1.757 NaN NaN
elr winter 2019 0.993 0.053 0.275 0.408 1.575 0.532 4.276
baseline all 0.989 0.052 0.345 0.411 3.200 NaN NaN
elr all 0.988 0.052 0.300 0.399 2.928 0.543 4.646

Extended logistic regression plots

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